README.md

LibreChat YAML Configuration Manager

This tool helps manage and maintain LibreChat YAML configuration files by providing automated updates for model lists and consistent YAML formatting.

Prerequisites

• Python 3.8 or higher
• pip (Python package installer)

Installation

1. Clone this repository:

git clone https://github.com/LibreChat-AI/librechat-config-yaml.git
cd librechat-config-yaml/scripts

2. Install required dependencies:

pip install -r requirements.txt

3. Copy the environment file and add your API keys:

cp .env.example .env

Edit .env and add your API keys for the services you want to use:

COHERE_API_KEY=your-cohere-key
DEEPSEEK_API_KEY=your-deepseek-key
# ... etc

Usage

Run the main update script:

python update.py

This will:

1. Prompt whether to update YAML formatting (should not be required)
2. Prompt whether to update model lists
3. Create backups before any modifications
4. Process all configuration files:
   • librechat-env-f.yaml
   • librechat-env-l.yaml
   • librechat-up-f.yaml
   • librechat-up-l.yaml
   • librechat-test.yaml

Individual Scripts

You can also run individual scripts directly:

Convert YAML formatting:

python convert_yaml_style.py

Update model lists:

python update_models.py

Directory Structure

librechat-config-yaml/
├── requirements.txt     # Python dependencies
├── README.md            # This file
├── scripts/             # Helper scripts
│   ├── README.md              # Scripts documentation
│   ├── update.py              # Main script
│   ├── convert_yaml_style.py  # Convert YAML formatting
│   ├── update_models.py       # Update model lists
│   ├── requirements.txt       # Python dependencies
│   ├── .env.example           # Example environment file
│   ├── .env                   # Your API keys (create this)
│   ├── fetch_apipie.py        # Fetch models from APIpie
│   ├── fetch_cohere.py        # Fetch models from Cohere
│   ├── fetch_deepseek.py      # Fetch models from Deepseek
│   ├── fetch_fireworks.py     # Fetch models from Fireworks
│   ├── fetch_github.py        # Fetch models from Github Models
│   ├── fetch_glhf.py          # Fetch models from GLHF.chat
│   ├── fetch_groq.py          # Fetch models from Groq
│   ├── fetch_huggingface.py   # Fetch models from HuggingFace
│   ├── fetch_hyperbolic.py    # Fetch models from Hyperbolic
│   ├── fetch_kluster.py       # Fetch models from Kluster
│   ├── fetch_mistral.py       # Fetch models from Mistral
│   ├── fetch_nanogpt.py       # Fetch models from NanoGPT
│   ├── fetch_nvidia.py        # Fetch models from Nvidia
│   ├── fetch_openrouter.py    # Fetch models from OpenRouter
│   ├── fetch_perplexity.py    # Fetch models from Perplexity
│   ├── fetch_sambanova.py     # Fetch models from SambaNova
│   ├── fetch_together.py      # Fetch models from Together.ai
│   ├── fetch_unify.py         # Fetch models from Unify
│   └── fetch_xai.py           # Fetch models from XAI
└── *.yaml               # LibreChat configuration files

Backup and Safety

• All scripts create .bak files before modifying any YAML files
• Logs are written to:
  • convert_yaml.log for YAML style conversion
  • update_models.log for model updates

Error Handling

• Failed operations are logged with detailed error messages
• The scripts will continue processing remaining files if one fails
• A summary is displayed after completion showing:
  • Successfully processed files
  • Failed operations
  • Model count updates

Supported Providers

The tool can update model lists from:

• APIpie
• Cohere
• Deepseek
• Fireworks
• Github Models
• GLHF.chat
• Groq
• HuggingFace
• Hyperbolic
• Kluster
• Mistral
• NanoGPT
• Nvidia
• OpenRouter
• Perplexity
• SambaNova
• Together.ai
• Unify
• XAI

Contributing

When adding new providers:

1. Create a new fetcher script in the scripts directory
2. Update the provider list in update_models.py
3. Add any required API keys to .env.example